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Found 5 papers, 5 papers with code
Language Models as Black-Box Optimizers for Vision-Language Models
We highlight the advantage of conversational feedback that incorporates both positive and negative prompts, suggesting that LLMs can utilize the implicit gradient direction in textual feedback for a more efficient search.
Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models
By repurposing class names as additional one-shot training samples, we achieve SOTA results with an embarrassingly simple linear classifier for vision-language adaptation.
PACS: A Dataset for Physical Audiovisual CommonSense Reasoning
Our paper takes a step towards real-world physical commonsense reasoning by contributing PACS: the first audiovisual benchmark annotated for physical commonsense attributes.
Street Crossing Aid Using Light-weight CNNs for the Visually Impaired
In this paper, we address an issue that the visually impaired commonly face while crossing intersections and propose a solution that takes form as a mobile application.
LYTNet: A Convolutional Neural Network for Real-Time Pedestrian Traffic Lights and Zebra Crossing Recognition for the Visually Impaired
LYTNet delivers both of the two most important pieces of information for the visually impaired to cross the road.
